Triple
T6307792
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ōiso |
E141421
|
entity |
| Predicate | hasMayor |
P185
|
FINISHED |
| Object |
Kenji Aiba
Kenji Aiba is a Japanese local politician who serves as the mayor of the town of Ōiso in Kanagawa Prefecture.
|
E940090
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Kenji Aiba | Statement: [Ōiso, hasMayor, Kenji Aiba]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kenji Aiba Context triple: [Ōiso, hasMayor, Kenji Aiba]
-
A.
Masaki Aiba
Masaki Aiba is a Japanese singer, actor, and television personality best known as a member of the popular boy band Arashi.
-
B.
Masato Otaka
Masato Otaka is a Japanese architect associated with the Metabolism movement, known for his contributions to postwar urban planning and visionary megastructure designs.
-
C.
Mako Komuro
Mako Komuro is a former Japanese imperial family member and niece of Emperor Naruhito who left royal status upon marrying commoner Kei Komuro.
-
D.
Toru Watanabe
Toru Watanabe is the introspective university student protagonist of Haruki Murakami’s novel "Norwegian Wood," whose coming-of-age story explores love, loss, and emotional turmoil in 1960s Tokyo.
-
E.
Katsuya Okada
Katsuya Okada is a Japanese politician who has served as leader of the Democratic Party of Japan and as Deputy Prime Minister.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Kenji Aiba Triple: [Ōiso, hasMayor, Kenji Aiba]
Generated description
Kenji Aiba is a Japanese local politician who serves as the mayor of the town of Ōiso in Kanagawa Prefecture.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kenji Aiba Target entity description: Kenji Aiba is a Japanese local politician who serves as the mayor of the town of Ōiso in Kanagawa Prefecture.
-
A.
Masaki Aiba
Masaki Aiba is a Japanese singer, actor, and television personality best known as a member of the popular boy band Arashi.
-
B.
Masato Otaka
Masato Otaka is a Japanese architect associated with the Metabolism movement, known for his contributions to postwar urban planning and visionary megastructure designs.
-
C.
Mako Komuro
Mako Komuro is a former Japanese imperial family member and niece of Emperor Naruhito who left royal status upon marrying commoner Kei Komuro.
-
D.
Toru Watanabe
Toru Watanabe is the introspective university student protagonist of Haruki Murakami’s novel "Norwegian Wood," whose coming-of-age story explores love, loss, and emotional turmoil in 1960s Tokyo.
-
E.
Katsuya Okada
Katsuya Okada is a Japanese politician who has served as leader of the Democratic Party of Japan and as Deputy Prime Minister.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69c008d00efc8190a36c05b4b4a3bf4b |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0647d38008190abaf96632712ddf9 |
completed | March 22, 2026, 9:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ef1243b14081909d07ab0ebb32cc68 |
completed | April 27, 2026, 7:37 a.m. |
| NEDg | Description generation | batch_69ef354b3b3c8190b1c91dbf9c705a7d |
completed | April 27, 2026, 10:07 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ef5170ce9881908f2ecf3d5ada809a |
completed | April 27, 2026, 12:07 p.m. |
Created at: March 22, 2026, 4:28 p.m.